Workshop - AI FORUM: presentation of technologies and application cases

Company speeches:

ELMEC GROUP - INDUVATION - ANALYTICS HUB - QUINDI - MYNT AI - AIPEX Labs - SIDERIUS – ZANIN

ELMEC GROUP SRL
From IDA data to artificial intelligence: how Elmec Group built its own tailor-made AI ecosystem.
Elmec Group tells how, starting from the energy and OEE data collected with Maxfone's IDA platform, a true artificial intelligence ecosystem was born — developed in-house and tailored to the company. An automated weekly report, built with AI on already validated data, became the solid foundation for new developments: quarterly dashboards, dedicated views for production and the first steps towards cost allocation, all the way to dedicated conversational assistants that answer direct questions about the dashboards. Not an isolated experiment, but an infrastructure that keeps growing — a concrete case of AI born on the shop floor and remaining at the service of those who make decisions.

INDUVATION
AI can reveal what your WMS hides from you
Between one scan and the next, waiting times, unnecessary routes and inefficiencies are concealed — things that traditional systems often fail to detect.
With Motion Mining, sensors and Artificial Intelligence make visible what is really happening in operational processes.
A new way to turn invisible activities into concrete data and improvement opportunities.

ANALYTICS HUB
From question to data: the AI that interrogates the company
From dashboards to conversational Business Intelligence
What if a business owner could query their company's data simply by asking a question? We will present a concrete case of AI applied to Business Intelligence, capable of understanding and integrating data from ERPs, databases and different company sources. From building the knowledge base to Data Quality, through to natural language responses: a new, secure and scalable way of turning company data into information that can be used in decision-making.

QUINDI
Artificial Intelligence in production decisions
Real-time production planning and management, with margin as the objective.
Every day we rely on real-time data to choose the best route. In the factory, how up to date is the data on which we base our decisions?
Quindi connects machines, manual processes and company systems to automatically collect data and use it in production planning and management.
Through industrial case studies and a demo of Quindi AI Scheduler, we will show how AI updates the plan as production conditions change, with a concrete objective: increasing operating margin.

MYNT AI S.r.l.
AfterCare: the AI agent that lightens the load for After Sales and Customer Service
It reads the customer's request, retrieves the previously given answer, and drafts a response with sources. The operator approves.
Abstract: After Sales offices have been answering the same questions for years, but each time they start from scratch: finding the answer costs more than writing it. AfterCare reads the incoming request, finds it in the technical documentation and historical records, and prepares the draft with cited sources; the operator checks and sends. Less time searching, consistent answers, know-how that stays in the company even when people change. Real case presented anonymously, project in progress.

AIPEX Labs
From Order to Cut-Ready File: An AI Agent for the Technical Office
(EN: From Order to Cut-Ready File: An AI Agent for the Technical Office)
The technical office of an Italian manufacturing company was losing between one hour and one and a half hours per order to manually redraw it into a cut-ready file — a bottleneck between order receipt and the CNC department. AIPEX Labs and MYNT AI developed an AI agent that reads the customer order (PDF) and the technical drawing (PDF, DXF or DWG) together and generates a fully dimensioned DXF file in two to three minutes, ready to be loaded directly onto the machine. Validated on real production jobs excluded from training, with 16 exact matches out of 16 on one product family and zero discrepancies on 43 jobs on a second family. AIPEX Labs led the project and developed the drawing recognition engine and DXF generation; MYNT AI developed the interface and production integration. The talk retraces how the two parts integrate and what was needed to move from a working prototype to a tool that the technical office truly trusts.

SIDERIUS – ZANIN
Interrogating the mind: Designing the perception of a product with data and AI.
Over 85% of purchasing decisions go through emotional and sensory processes: the consumer cannot say why they choose. Siderius designs brand perception starting from data, integrating behavioural research, cognitive sciences and artificial intelligence. We present the platform we are developing to predict how a product will be perceived even before it is produced, and the FlyOver case for Distilleria Zanin 1895: a line conceived, developed and launched in three months, today internationally award-winning.